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Elucidation of the neutralizing antibody evasion of emergent SARS-CoV-2 Omicron sub-lineages using structural analysis

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (82030046). We acknowledge the support from National Supercomputer Center, Guangzhou with the Tianhe-2 supercomputer. We would also like to thank EditChecks (https://editchecks.com.cn/) for providing linguistic assistance during the preparation of this manuscript.

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Author notes

  1. Contributed equally to this work

Authors and Affiliations

  1. State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Department of Experimental Research, Sun Yat-sen University Cancer Center, Sun Yat-sen University, Guangzhou, 510060, China

    Cong Sun, Yuan-Tao Liu, Yin-Feng Kang, Chu Xie, Shu-Xin Li & Mu-Sheng Zeng

  2. National Supercomputer Center in Guangzhou, School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510006, China

    Yu-Tong Lu

Authors
  1. Cong Sun
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  2. Yuan-Tao Liu
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  3. Yin-Feng Kang
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  4. Chu Xie
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  5. Shu-Xin Li
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Corresponding authors

Correspondence to Cong Sun or Mu-Sheng Zeng.

Ethics declarations

Compliance and ethics The author(s) declare that they have no conflict of interest. All data are available in the manuscript or the supplementary materials. The flexddG pipeline used in this study is available at the Github repository (https://github.com/bigtaotao/Omicron_Sublineages_Analysis). All structural representations were generated using ChimeraX-1.1.1 or PyMOL. The protein complex structures used in this study are available at PDB (Accession numbers: 7mmo, 6wps, 6xdg, 7kmg, 7c01, 7cm4, 8d8q, 8gx9, 7u2d, 7ch4, 7k8z, 7k90, 7sbu, 7dk0, 7cwt, 7byr, 7b3o, 7ral, 7c2l, 7l2e, and 7rw2).

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Sun, C., Liu, YT., Kang, YF. et al. Elucidation of the neutralizing antibody evasion of emergent SARS-CoV-2 Omicron sub-lineages using structural analysis. Sci. China Life Sci. 66, 2935–2938 (2023). https://doi.org/10.1007/s11427-023-2393-3

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  • DOI: https://doi.org/10.1007/s11427-023-2393-3

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